International Council for Harmonisation E6(R2) addendum: Challenges of implementation

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Arun BhattDOI:10.4103/picr.PICR_124_17 PMID:29109932

The International Council for Harmonisation (ICH) E6 – good clinical practice (GCP) (R2) addendum – was released in 2016 to encourage implementation of improved approaches for the management of clinical trials. The changes in different sections include new approaches – quality management system, risk-based monitoring with emphasis on human subject protection, and data integrity. The article discusses challenges in adoption and implementation of the changes in ICH GCP guideline for clinical trial stakeholders.

Purpose: The International Committee of Medical Journal Editors mandates trial registration as a precondition for publication. Growing evidence indicates that information in registry may not correlate with eventual publication. The present study was carried out with the objective of comparing content of Randomized Controlled Trials (RCTs) published in one year in the Journal of the American Medical Association (JAMA), with the information contained in trial registries.
Methods: All RCTs published in JAMA in 2013 were included. 11 data set items were matched for content between registry entry and published RCT: Title, Primary and Secondary Objectives, Study type, Inclusion and Exclusion Criteria, Treatment Age Group, Follow up, Sample Size, Primary and Secondary Outcomes. A fully correct match was scored 2, partially correct 1 and incorrect 0. Thus, maximum possible score for each paper was number of items multiplied by 2, i.e., 22.
Results: The median [range] total score achieved by RCTs was 15. No RCT achieved a perfect score of 22. The largest proportion of RCTs reported secondary objectives, study type, treatment age group, follow up, sample size and primary outcomes fully correctly. However, only 13.5 %, 12 % and 13.5 % of RCTs were a perfect match with registry entries in terms of title, primary objective and secondary outcomes respectively. Almost three quarters did not match perfectly in selection criteria.
Conclusion: There exist discrepancies between trial registration and published paper even in a high impact factor journal. Both authors and editors should adhere to CONSORT guidelines to ensure transparency of published research.

Background: India continues to contribute disproportionately to the global burden of disease and public health research output from India is also known to be not commensurate with her healthcare needs. We carried out the present study to assess if clinical trials were in line with the health care needs of the country by auditing the clinical trials registry of India.
Materials and Methods: All the clinical studies registered in CTRI between July 20, 2007 and December 31, 2015 were searched in the “Trial Search” section. The total number of studies, their phases of development, and therapeutic areas were assessed. Trials in each therapeutic area was compared with the disease burden (DALYs) in that area taken from Global Health Estimates [2014] Summary Tables of the WHO. The number of trials conducted per state in India was also compared with the population of that state [Census 2011].
Results: A total of 6474 studies were registered of which 3325 (51.4%) were clinical trials. The state of Maharashtra had the highest number trials [16.4%] followed by Karnataka ( 11.6%) and Tamil Nadu (10%). Populous states like Uttar Pradesh (5.3%) and Bihar (1.4%) had far fewer trials. The largest number of trials was in the area of cancer (16.4%), followed by diabetes (12.1%) and cardiovascular diseases (10.1%). Infectious and parasitic diseases had the highest DALYs (82,681) and ranked first in disease burden but accounted for only 5% of the total trials and ranked 7th according to number of trials. Cancer ranked first in the number of trials (16.4%), but ranked 6th based on DALYs.
Conclusion: Clinical trials conducted in India are not in consonance with her health care needs. Strengthening the capacity for conducting trials in the populous states and the north-eastern part of the country is necessary to allow a more equitable selection of participants. The government should introduce policies to encourage new drug development in areas where needed the most.

Objective: The objective of this study is to assess the postmarketing status: Efficacy and safety drugs and biologics related with cancer approved under expedited review.
Methods: This observational, analytical study was carried between January and April 2016 by the Department of Pharmacology and Medical Oncology, Saveetha Medical College. Drugs approved under expedited review, fast-track status and its association with anti-cancer effects, postmarketing efficacy and safety, propensity to induce the second tumor was noted. Drug approval status and average time of review process were obtained from the United States-Food and Drug Administration (FDA), Center for Drugs and Biologics Center (Center for Drug Evaluation and Research and Center for Biologics Evaluation and Research). Postmarketing adverse events and safety issues were collected FDA adverse effects reporting system. Further, evidence efficacy and safety of drugs were taken from various meta-analysis, reports on BioMed journals, and Cochrane systematic reviews.
Results: In the last 5 years, 166 products were approved by expedited review. Out of 166, 48 (28.9%) drugs/biologics are anticancer drugs and drugs used in precancerous conditions. The average time of review varies from19 months to 8.2 months. Out of these 48 molecules, 37 (77%) molecules received serious adverse event alert. Positive correlation is seen between average time of review and number of adverse events reported. Seven (14.5%) drugs were proven to induce second tumor among receivers.
Conclusion: Although expedited review facilitates faster approval of drugs; selection and assessment criteria should be stringent to prevent clinical failure, serious adverse effects of such drugs exposed to many individuals. Focus should be given developing chemosensitizing molecule and evaluation of metronomic regimen which is being more optimistic in current cancer therapeutics.

Introduction: Concomitant use of multiple drugs is often indicated to manage comorbid conditions and enhance efficacy. Such concomitant use of multiple drugs (five or more drugs) has been defined as “polypharmacy.” Polypharmacy has been associated with adverse consequences such as greater healthcare costs, increased risk of adverse drug events, drug–drug interactions (DDIs), medication nonadherence, reduced functional capacity, and multiple geriatric syndromes. This study evaluated number of potential harmful DDIs due to polypharmacy.
Materials and Methods: A prospective, cross-sectional, observational study was performed from July 2011 to June 2012. Approval was obtained from the Institutional Ethics Committee, Goa Medical College. Drug interactions were identified using a computerized DDI database system Lexi-Comp version: 2.4.1. Quantitative data analysis was done by the SPSS for Windows version 17.0.
Results: Seven hundred and fifty-one out of 5424 (13.85%) prescriptions were observed to have polypharmacy with highest rates observed in the Department of Medicine. The median age of patients was 55.60 ± 13.86 (range 10–108 years). A total number of drugs per prescription ranged from minimum of 5 to maximum of 16 drugs, with an average of 7.96 ± 1.75. A large number of 596 prescriptions contained 6–9 drugs per prescription. Drugs involved in potential DDIs in our study included aspirin, antacids, beta-blockers, 3-hydroxy-3-methylglutaryl-coenzyme reductase inhibitors, calcium channel blockers, angiotensin-converting enzyme inhibitors, ondansetron, and H2 blockers.
Conclusion: Patients taking multiple medications experience unique pharmacotherapy. Personalized drug prescribing strategies and close monitoring of patients taking drugs with potential DDIs are keys to optimal therapeutic result.

Agreement between measurements refers to the degree of concordance between two (or more) sets of measurements. Statistical methods to test agreement are used to assess inter-rater variability or to decide whether one technique for measuring a variable can substitute another. In this article, we look at statistical measures of agreement for different types of data and discuss the differences between these and those for assessing correlation.

Pharmacovigilance (PV) has grown significantly in India in the last couple of decades. The etymological roots for the word “pharmacovigilance” are “Pharmakon” (Greek for drug) and “Vigilare” (Latin for to keep watch). It relies on information gathered from the collection of individual case safety reports and other pharmacoepidemiological data. The PV data processing cycle starts with data collection in computerized systems followed by complete data entry which includes adverse event coding, drug coding, causality and expectedness assessment, narrative writing, quality control, and report submissions followed by data storage and maintenance. A case processor plays an important role in conducting these various tasks. The case processor should also manage drug safety information, possess updated knowledge about global drug safety regulations, summarize clinical safety data, participate in meetings, write narratives with medical input from a physician, report serious adverse events to the regulatory authorities, participate in the training of operational staff on drug safety issues, quality control work of other staff in the department, and take on any other task as assigned by the manager or medical director within the capabilities of the drug safety associate. There can be challenges while handling all these tasks at a time, hence the associate will have to maintain a balance to overcome them and keep on updating their knowledge on drug safety regulations, which in turn, would help in increasing their learning curve.